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Clean-up; PEP8-compliance
This commit is contained in:
parent
fef87a6657
commit
a5eb072d4a
1 changed files with 152 additions and 172 deletions
324
pydsf.py
324
pydsf.py
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@ -1,18 +1,14 @@
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#! /usr/bin/env python2
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#! /usr/bin/env python
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# -*- coding: utf-8 -*-
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import csv
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import random
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try:
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import matplotlib as mpl
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#import mpl_toolkits.axes_grid
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import mpl_toolkits.axes_grid1
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mpl.use('Qt5Agg')
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mpl.interactive(True)
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import matplotlib.ticker as ticker
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import matplotlib.patches as mpatches
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import matplotlib.gridspec as gridspec
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except ImportError:
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raise ImportError('----- Matplotlib must be installed. -----')
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@ -27,13 +23,14 @@ except ImportError:
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raise ImportError('----- NumPy must be installed. -----')
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try:
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from scipy.signal import filtfilt, butter, find_peaks_cwt
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from scipy.signal import filtfilt, butter
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from scipy import interpolate
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except ImportError:
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raise ImportError('----- SciPy must be installed. -----')
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class Well:
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def __init__(self, owner):
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self.owner = owner
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self.name = None
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@ -59,7 +56,8 @@ class Well:
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"""
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Calculate a spline that represents the smoothed data points
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"""
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spline = interpolate.InterpolatedUnivariateSpline(self.owner.temprange, y)
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t_range = self.owner.temprange
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spline = interpolate.InterpolatedUnivariateSpline(t_range, y)
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return spline
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def calc_derivatives(self, spline='filtered'):
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@ -87,8 +85,12 @@ class Well:
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# First assume that the well is denatured
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self.owner.denatured_wells.append(self)
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if self.owner.tm_cutoff_low != self.owner.t1 or self.owner.tm_cutoff_high != self.owner.t1:
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x = np.arange(self.owner.tm_cutoff_low, self.owner.tm_cutoff_high + 1, self.owner.dt, dtype=np.dtype(np.float))
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if (self.owner.tm_cutoff_low != self.owner.t1 or
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self.owner.tm_cutoff_high != self.owner.t1):
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x = np.arange(self.owner.tm_cutoff_low,
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self.owner.tm_cutoff_high + 1,
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self.owner.dt,
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dtype=np.dtype(np.float))
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x = self.owner.temprange
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y = self.derivatives[1]
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@ -107,17 +109,22 @@ class Well:
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max_y = y[peak]
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max_i = peak
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if y[max_i] > 0: # if value of second derivative is positive, choose identified position as peak candidate
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if y[max_i] > 0:
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# if value of second derivative is positive, choose identified
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# position as peak candidate
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tm = x[max_i]
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else:
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return np.NaN # else discard
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return np.NaN # else discard
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except:
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return np.NaN # In case of error, return no peak
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try:
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if tm and tm >= self.owner.tm_cutoff_low and tm <= self.owner.tm_cutoff_high:
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tm = round(peakutils.interpolate(x, y, width=3, ind=[max_i])[0], 2)
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self.owner.denatured_wells.remove(self) # If everything is fine, remove the denatured flag
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if (tm and tm >= self.owner.tm_cutoff_low and
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tm <= self.owner.tm_cutoff_high):
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tm = round(peakutils.interpolate(x, y, width=3,
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ind=[max_i])[0], 2)
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self.owner.denatured_wells.remove(self)
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# If everything is fine, remove the denatured flag
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return tm # and return the Tm
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else:
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return np.NaN # otherwise, return NaN
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@ -126,33 +133,41 @@ class Well:
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def is_denatured(self):
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"""
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Check if the well is denatured. Returns true if the well has been already flagged as
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denatured, no Tm was found, or if the initial signal intensity is above a user definded
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threshold.
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Check if the well is denatured. Returns true if the well has been
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already flagged as denatured, no Tm was found, or if the initial
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signal intensity is above a user definded threshold.
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"""
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denatured = True # Assumption is that the well is denatured
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if self in self.owner.denatured_wells: # check if the well is already flagged as denatured
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if self in self.owner.denatured_wells:
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# check if the well is already flagged as denatured
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return denatured # return true if it is
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if self.tm and (self.tm <= self.owner.tm_cutoff_low or self.tm >= self.owner.tm_cutoff_high):
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if self.tm and (self.tm <= self.owner.tm_cutoff_low or
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self.tm >= self.owner.tm_cutoff_high):
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denatured = True
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return denatured
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for i in self.derivatives[1]: # Iterate over all points in the first derivative
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for i in self.derivatives[1]:
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# Iterate over all points in the first derivative
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if i > 0: # If a positive slope is found
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denatured = False # set denatured flag to False
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reads = int(round(self.owner.reads / 10)) # How many values should be checked against the signal threshold:
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reads = int(round(self.owner.reads / 10))
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# How many values should be checked against the signal threshold:
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# 1/10 of the total number of data point
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read = 0 # Initialize running variable representing the current data point
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read = 0
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# Initialize running variable representing the current data point
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if not denatured:
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for j in self.filtered: # Iterate over the filtered data
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if self.owner.signal_threshold: # If a signal threshold was defined
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if j > self.owner.signal_threshold and read <= reads: # iterate over 1/10 of all data points
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if self.owner.signal_threshold:
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# If a signal threshold was defined
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if j > self.owner.signal_threshold and read <= reads:
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# iterate over 1/10 of all data points
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# and check for values larger than the threshold.
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denatured = True # Set flag to True if a match is found
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denatured = True
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# Set flag to True if a match is found
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print("{}: {}".format(self.name, j))
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return denatured # and return
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read += 1
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@ -178,8 +193,10 @@ class Well:
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class Experiment:
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def __init__(self, type, gui=None, files=None, replicates=None, t1=25, t2=95, dt=1, cols=12, rows=8,
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cutoff_low=None, cutoff_high=None, signal_threshold=None, color_range=None, baseline_correction=False):
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def __init__(self, type, gui=None, files=None, replicates=None, t1=25,
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t2=95, dt=1, cols=12, rows=8, cutoff_low=None,
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cutoff_high=None, signal_threshold=None, color_range=None,
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baseline_correction=False):
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self.replicates = replicates
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self.cols = cols
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self.rows = rows
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@ -216,16 +233,22 @@ class Experiment:
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i = 1
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for file in files:
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plate = Plate(type=self.type, owner=self, filename=file, t1=self.t1, t2=self.t2, dt=self.dt, cols=self.cols,
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rows=self.rows, cutoff_low=self.tm_cutoff_low, cutoff_high=self.tm_cutoff_high,
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signal_threshold=self.signal_threshold, color_range=self.color_range)
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plate = Plate(type=self.type, owner=self, filename=file,
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t1=self.t1, t2=self.t2, dt=self.dt, cols=self.cols,
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rows=self.rows, cutoff_low=self.tm_cutoff_low,
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cutoff_high=self.tm_cutoff_high,
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signal_threshold=self.signal_threshold,
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color_range=self.color_range)
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plate.id = i
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self.plates.append(plate)
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i += 1
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if len(files) > 1:
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self.avg_plate = Plate(type=self.type, owner=self, filename=None, t1=self.t1, t2=self.t2, dt=self.dt,
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cols=self.cols, rows=self.rows, cutoff_low=self.tm_cutoff_low,
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cutoff_high=self.tm_cutoff_high, signal_threshold=self.signal_threshold,
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self.avg_plate = Plate(type=self.type, owner=self, filename=None,
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t1=self.t1, t2=self.t2, dt=self.dt,
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cols=self.cols, rows=self.rows,
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cutoff_low=self.tm_cutoff_low,
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cutoff_high=self.tm_cutoff_high,
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signal_threshold=self.signal_threshold,
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color_range=self.color_range)
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self.avg_plate.id = 'average'
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@ -235,10 +258,6 @@ class Experiment:
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if len(self.plates) > 1:
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# self.tm_replicates = np.zeros( self.wellnum, dtype=float )
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# self.tm_replicates_sd = np.zeros( self.wellnum, dtype=float )
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for i in range(self.wellnum):
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tmp = []
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for plate in self.plates:
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@ -247,17 +266,17 @@ class Experiment:
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if plate.wells[i] not in plate.denatured_wells:
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tmp.append(tm)
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if len(tmp) > 0:
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# self.avg_plate.wells[i].tm = (sum(tmp)/len(tmp))
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self.avg_plate.wells[i].tm = np.mean(tmp)
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self.avg_plate.wells[i].tm_sd = np.std(tmp)
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# self.tm_replicates[i] = (sum(tmp)/len(tmp))
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else:
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self.avg_plate.denatured_wells.append(self.avg_plate.wells[i])
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append_well = self.avg_plate.wells[i]
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self.avg_plate.denatured_wells.append(append_well)
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class Plate:
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def __init__(self, type, owner, id=None, filename=None, replicates=None, t1=None, t2=None, dt=None, cols=12, rows=8,
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cutoff_low=None, cutoff_high=None, signal_threshold=None, color_range=None):
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def __init__(self, type, owner, id=None, filename=None, replicates=None,
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t1=None, t2=None, dt=None, cols=12, rows=8, cutoff_low=None,
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cutoff_high=None, signal_threshold=None, color_range=None):
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self.cols = cols
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self.rows = rows
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self.owner = owner
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@ -305,7 +324,6 @@ class Plate:
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well = Well(owner=self)
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self.wells.append(well)
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def analytikJena(self):
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"""
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Data processing for Analytik Jena qTower 2.0 export files
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@ -331,6 +349,7 @@ class Plate:
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try:
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# Try to access data file in the given path
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with open(self.filename) as f:
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f.close()
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pass
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except IOError as e:
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# If the file is not found, or not accessible: abort
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@ -371,12 +390,18 @@ class Plate:
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def write_avg_tm_table(self, filename):
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with open(filename, 'w') as f:
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f.write('#{:<4s}{:>13s}{:>13s}\n'.format('"ID"', '"Tm [°C]"', '"SD"'))
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f.write('#{:<4s}{:>13s}{:>13s}\n'.format('"ID"',
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'"Tm [°C]"',
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'"SD"'))
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for well in self.wells:
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if np.isnan(well.tm) or well in self.denatured_wells:
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f.write('{:<5s}{:>12s}{:>12s}\n'.format(well.name, 'NaN', 'NaN'))
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f.write('{:<5s}{:>12s}{:>12s}\n'.format(well.name,
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'NaN',
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'NaN'))
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else:
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f.write('{:<5s}{:>12s}{:>12s}\n'.format(well.name, str(well.tm), str(well.tm_sd)))
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f.write('{:<5s}{:>12s}{:>12s}\n'.format(well.name,
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str(well.tm),
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str(well.tm_sd)))
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def write_raw_table(self, filename):
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with open(filename, 'w') as f:
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@ -391,7 +416,8 @@ class Plate:
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f.write('{:<10s}'.format(str(t)))
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for well in self.wells:
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d = well.raw[i]
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f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
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d_rounded = float(np.round(d, decimals=3))
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f.write('{:>-15.3f}'.format(d_rounded))
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f.write('\n')
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i += 1
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@ -408,7 +434,8 @@ class Plate:
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f.write('{:<10s}'.format(str(t)))
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for well in self.wells:
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d = well.filtered[i]
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f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
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d_rounded = float(np.round(d, decimals=3))
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f.write('{:>-15.3f}'.format(d_rounded))
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f.write('\n')
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i += 1
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@ -425,7 +452,8 @@ class Plate:
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f.write('{:<10s}'.format(str(t)))
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for well in self.wells:
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d = well.derivatives[1][i]
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f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
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d_rounded = float(np.round(d, decimals=3))
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f.write('{:>-15.3f}'.format(d_rounded))
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f.write('\n')
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i += 1
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@ -438,6 +466,7 @@ class Plate:
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def update_progress_bar(bar, value):
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bar.setValue(value)
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class PlotResults():
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def plot_tm_heatmap_single(self, plate, widget):
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@ -451,18 +480,23 @@ class PlotResults():
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c_values = [] # Array holding the color values aka Tm
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dx_values = []
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dy_values = []
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dc_values = []
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canvas = widget.canvas
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canvas.clear()
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for well in plate.wells: # Iterate over all wells
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if well not in plate.denatured_wells: # Check if well is denatured (no Tm found)
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if well not in plate.denatured_wells:
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# Check if well is denatured (no Tm found)
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c = well.tm # If not, set color to Tm
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if c < plate.tm_cutoff_low: # Check if Tm is lower that the cutoff
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c = plate.tm_cutoff_low # If it is, set color to cutoff
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elif c > plate.tm_cutoff_high: # Check if Tm is higher that the cutoff
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c = plate.tm_cutoff_high # If it is, set color to cutoff
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if c < plate.tm_cutoff_low:
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# Check if Tm is lower that the cutoff
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c = plate.tm_cutoff_low
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# If it is, set color to cutoff
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elif c > plate.tm_cutoff_high:
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# Check if Tm is higher that the cutoff
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c = plate.tm_cutoff_high
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# If it is, set color to cutoff
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else: # If the plate is denatured
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c = plate.tm_cutoff_low # Set its color to the low cutoff
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c = plate.tm_cutoff_low
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# Set its color to the low cutoff
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dx_values.append(x)
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dy_values.append(y)
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x_values.append(x) # Add values to the respective arrays
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@ -476,15 +510,22 @@ class PlotResults():
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fig1 = canvas.fig # new figure
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ax1 = fig1.add_subplot(1, 1, 1) # A single canvas
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ax1.autoscale(tight=True) # Scale plate size
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ax1.xaxis.set_major_locator(ticker.MaxNLocator(plate.cols + 1)) # n columns
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ax1.yaxis.set_major_locator(ticker.MaxNLocator(plate.rows + 1)) # n rows
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ax1.xaxis.set_major_locator(ticker.MaxNLocator(plate.cols + 1))
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# n columns
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ax1.yaxis.set_major_locator(ticker.MaxNLocator(plate.rows + 1))
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# n rows
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if plate.color_range:
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cax = ax1.scatter(x_values, y_values, s=305, c=c_values, marker='s', vmin=plate.color_range[0],
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vmax=plate.color_range[1]) # plot wells and color using the colormap
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# plot wells and color using the colormap
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cax = ax1.scatter(x_values, y_values, s=305, c=c_values,
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marker='s', vmin=plate.color_range[0],
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vmax=plate.color_range[1])
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else:
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cax = ax1.scatter(x_values, y_values, s=305, c=c_values, marker='s') # plot wells and color using the colormap
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# plot wells and color using the colormap
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cax = ax1.scatter(x_values, y_values, s=305, c=c_values,
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marker='s')
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cax2 = ax1.scatter(dx_values, dy_values, s=80, c='white', marker='x', linewidths=(1.5,))
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ax1.scatter(dx_values, dy_values, s=80, c='white', marker='x',
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linewidths=(1.5,))
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ax1.invert_yaxis() # invert y axis to math plate layout
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cbar = fig1.colorbar(cax) # show colorbar
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ax1.set_xlabel('Columns') # set axis and colorbar label
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@ -506,45 +547,57 @@ class PlotResults():
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canvas = widget.canvas
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canvas.clear()
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fig2 = canvas.fig # new figure
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fig2.suptitle('Individual Derivatives (plate #{})'.format(str(plate.id))) # set title
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# set title
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fig2.suptitle(
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'Individual Derivatives (plate #{})'.format(str(plate.id)))
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for plot_num in range(1, plate.wellnum + 1): # iterate over all wells
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well = plate.wells[plot_num - 1] # get single well based on current plot number
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ax = fig2.add_subplot(plate.rows, plate.cols, plot_num) # add new subplot
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well = plate.wells[plot_num - 1]
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# get single well based on current plot number
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ax = fig2.add_subplot(plate.rows, plate.cols, plot_num)
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# add new subplot
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ax.autoscale(tight=True) # scale to data
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ax.set_title(well.name, size='xx-small') # set title of current subplot to well identifier
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ax.set_title(well.name, size='xx-small')
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# set title of current subplot to well identifier
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if well in plate.denatured_wells:
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ax.patch.set_facecolor('#FFD6D6')
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if plot_num == plate.wellnum - plate.cols + 1: # add axis label to the subplot in the bottom left corner of the figure
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# add axis label to the subplot in the bottom left corner of the
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# figure
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||||
if plot_num == plate.wellnum - plate.cols + 1:
|
||||
ax.set_xlabel(u'T [°C]', size='xx-small')
|
||||
ax.set_ylabel('dI/dT', size='xx-small')
|
||||
|
||||
x = plate.temprange # set values for the x axis to the given temperature range
|
||||
# set values for the x axis to the given temperature range
|
||||
x = plate.temprange
|
||||
if well.baseline_correction:
|
||||
print(well.baseline)
|
||||
y = well.derivatives[1] - well.baseline
|
||||
else:
|
||||
y = well.derivatives[1] # grab y values from the first derivative of the well
|
||||
# grab y values from the first derivative of the well
|
||||
y = well.derivatives[1]
|
||||
|
||||
ax.xaxis.set_major_locator(ticker.MaxNLocator(4)) # only show three tickmarks on both axes
|
||||
# only show three tickmarks on both axes
|
||||
ax.xaxis.set_major_locator(ticker.MaxNLocator(4))
|
||||
ax.yaxis.set_major_locator(ticker.MaxNLocator(4))
|
||||
if well not in plate.denatured_wells: # check if well is denatured (without determined Tm)
|
||||
# check if well is denatured (without determined Tm)
|
||||
if well not in plate.denatured_wells:
|
||||
tm = well.tm # if not, grab its Tm
|
||||
else:
|
||||
tm = np.NaN # else set Tm to np.NaN
|
||||
if tm:
|
||||
ax.axvline(x=tm) # plot vertical line at the Tm
|
||||
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8', alpha=0.5) # shade lower cutoff area
|
||||
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8', alpha=0.5) # shade higher cutoff area
|
||||
for label in ax.get_xticklabels() + ax.get_yticklabels(): # set fontsize for all tick labels to xx-small
|
||||
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8',
|
||||
alpha=0.5) # shade lower cutoff area
|
||||
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8',
|
||||
alpha=0.5) # shade higher cutoff area
|
||||
# set fontsize for all tick labels to xx-small
|
||||
for label in ax.get_xticklabels() + ax.get_yticklabels():
|
||||
label.set_fontsize('xx-small')
|
||||
|
||||
cax = ax.plot(x, y) # plot data to the current subplot
|
||||
ax.plot(x, y) # plot data to the current subplot
|
||||
canvas.draw()
|
||||
|
||||
|
||||
def plot_raw(self, plate, widget):
|
||||
"""
|
||||
Plot raw data (Fig. 3)
|
||||
|
|
@ -558,108 +611,35 @@ class PlotResults():
|
|||
fig = canvas.fig
|
||||
fig.suptitle('Raw Data (plate #{})'.format(str(plate.id)))
|
||||
|
||||
grid = mpl_toolkits.axes_grid1.Grid(fig, 111, nrows_ncols=(plate.rows, plate.cols), axes_pad=(0.1, 0.25), add_all=True, share_x=True, share_y=True, share_all=True)
|
||||
grid = mpl_toolkits.axes_grid1.Grid(fig, 111,
|
||||
nrows_ncols=(plate.rows,
|
||||
plate.cols),
|
||||
axes_pad=(0.1, 0.25),
|
||||
add_all=True,
|
||||
share_x=True,
|
||||
share_y=True,
|
||||
share_all=True)
|
||||
for i in range(plate.wellnum):
|
||||
well = plate.wells[i]
|
||||
x = plate.temprange # set values for the x axis to the given temperature range
|
||||
y = well.raw # grab y values from the raw data of the well
|
||||
# set values for the x axis to the given temperature range
|
||||
x = plate.temprange
|
||||
# grab y values from the raw data of the well
|
||||
y = well.raw
|
||||
ax = grid[i]
|
||||
|
||||
#ax = fig.add_subplot(plate.rows, plate.cols, i+1)
|
||||
ax.set_title(well.name, size=6) # set title of current subplot to well identifier
|
||||
# set title of current subplot to well identifier
|
||||
ax.set_title(well.name, size=6)
|
||||
if well in plate.denatured_wells:
|
||||
ax.patch.set_facecolor('#FFD6D6')
|
||||
ax.xaxis.set_major_locator(ticker.MaxNLocator(4)) # only show three tickmarks on both axes
|
||||
# only show three tickmarks on both axes
|
||||
ax.xaxis.set_major_locator(ticker.MaxNLocator(4))
|
||||
ax.yaxis.set_major_locator(ticker.MaxNLocator(4))
|
||||
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8', alpha=0.5) # shade lower cutoff area
|
||||
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8', alpha=0.5) # shade higher cutoff area
|
||||
for label in ax.get_xticklabels() + ax.get_yticklabels(): # set fontsize for all tick labels to xx-small
|
||||
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8',
|
||||
alpha=0.5) # shade lower cutoff area
|
||||
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8',
|
||||
alpha=0.5) # shade higher cutoff area
|
||||
# set fontsize for all tick labels to xx-small
|
||||
for label in ax.get_xticklabels() + ax.get_yticklabels():
|
||||
label.set_fontsize(6)
|
||||
ax.plot(x, y)
|
||||
fig.tight_layout()
|
||||
canvas.draw()
|
||||
|
||||
#ax = grid[i]
|
||||
#ax.axhline(color='r')
|
||||
#ax.autoscale(enable=True, axis='y', tight=True)
|
||||
#ax.set_title(well.name, size='xx-small')
|
||||
#ax.plot(x, 1000*np.random.random(76))
|
||||
#ax.set_yscale('log')
|
||||
|
||||
#for plot_num in range(1, plate.wellnum + 1):
|
||||
# well = plate.wells[plot_num - 1]
|
||||
# #ax = fig.add_subplot(plate.rows, plate.cols, plot_num)
|
||||
# ax.autoscale(tight=True)
|
||||
# ax.plot(plate.temprange, well.raw)
|
||||
# ax.set_title(well.name, size='xx-small')
|
||||
# if well in plate.denatured_wells:
|
||||
# ax.patch.set_facecolor('#FFD6D6')
|
||||
|
||||
|
||||
|
||||
#for plot_num in range(1, plate.wellnum + 1):
|
||||
# ax = fig.add_subplot(plate.rows, plate.cols, plot_num)
|
||||
# ax.autoscale(tight=True)
|
||||
|
||||
# fig3 = canvas.fig # new figure
|
||||
# fig3.suptitle('Raw Data (plate #{})'.format(str(plate.id))) # set title
|
||||
#
|
||||
# for plot_num in range(1, plate.wellnum + 1): # iterate over all wells
|
||||
# well = plate.wells[plot_num - 1] # get single well based on current plot number
|
||||
# ax = fig3.add_subplot(plate.rows, plate.cols, plot_num) # add new subplot
|
||||
# ax = fig3.add_axes(plate.rows, plate.cols, plot_num)
|
||||
# ax.autoscale(tight=True) # scale to data
|
||||
# ax.set_title(well.name, size='xx-small') # set title of current subplot to well identifier
|
||||
#
|
||||
# if well in plate.denatured_wells:
|
||||
# ax.patch.set_facecolor('#FFD6D6')
|
||||
#
|
||||
# if plot_num == plate.wellnum - plate.cols + 1: # add axis label to the subplot in the bottom left corner of the figure
|
||||
# ax.set_xlabel(u'T [°C]', size='xx-small')
|
||||
# ax.set_ylabel('I', size='xx-small')
|
||||
#
|
||||
# x = plate.temprange # set values for the x axis to the given temperature range
|
||||
# y = well.raw # grab y values from the raw data of the well
|
||||
#
|
||||
# ax.xaxis.set_major_locator(ticker.MaxNLocator(4)) # only show three tickmarks on both axes
|
||||
# ax.yaxis.set_major_locator(ticker.MaxNLocator(4))
|
||||
# ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8', alpha=0.5) # shade lower cutoff area
|
||||
# ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8', alpha=0.5) # shade higher cutoff area
|
||||
# for label in ax.get_xticklabels() + ax.get_yticklabels(): # set fontsize for all tick labels to xx-small
|
||||
# label.set_fontsize('xx-small')
|
||||
#
|
||||
# cax = ax.plot(x, y) # plot data to the current subplot
|
||||
|
||||
|
||||
|
||||
# def _plot_wrapper(self, plot, plate):
|
||||
#
|
||||
# if plot == 'raw':
|
||||
# fig, ax = self._plot_raw(plate)
|
||||
# elif plot == 'derivative':
|
||||
# fig, ax = self._plot_derivative(plate)
|
||||
# elif plot == 'tm_heatmap':
|
||||
# fig, ax = self._plot_tm_heatmap_single(plate)
|
||||
# else:
|
||||
# raise NotImplementedError
|
||||
# fig = None
|
||||
# ax = None
|
||||
# return (fig, ax)
|
||||
#
|
||||
# def plot_all(self):
|
||||
#
|
||||
# figures = []
|
||||
#
|
||||
# for plate in self.experiment.plates:
|
||||
#
|
||||
# figures.append(self._plot_wrapper('raw', plate))
|
||||
# figures.append(self._plot_wrapper('derivative', plate))
|
||||
# figures.append(self._plot_wrapper('tm_heatmap', plate))
|
||||
#
|
||||
# if len(self.experiment.plates) > 1:
|
||||
# figures.append(self._plot_wrapper('tm_heatmap', self.experiment.avg_plate))
|
||||
#
|
||||
# return figures
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue